Purpose: The selective MET inhibitor capmatinib is being investigated in multiple clinical trials, both as a single agent and in combination. Here, we describe the preclinical data of capmatinib, which supported the clinical biomarker strategy for rational patient selection. Experimental Design: The selectivity and cellular activity of capmatinib were assessed in large cellular screening panels. Antitumor efficacy was quantified in a large set of cell line-or patient-derived xenograft models, testing single-agent or combination treatment depending on the genomic profile of the respective models. Results: Capmatinib was found to be highly selective for MET over other kinases. It was active against cancer models that are characterized by MET amplification, marked MET overexpression, MET exon 14 skipping mutations, or MET activation via expression of the ligand hepatocyte growth factor (HGF). In cancer models where MET is the dominant oncogenic driver, anticancer activity could be further enhanced by combination treatments, for example, by the addition of apoptosis-inducing BH3 mimetics. The combinations of capmatinib and other kinase inhibitors resulted in enhanced anticancer activity against models where MET activation cooccurred with other oncogenic drivers, for example EGFR activating mutations. Conclusions: Activity of capmatinib in preclinical models is associated with a small number of plausible genomic features. The low fraction of cancer models that respond to capmatinib as a single agent suggests that the implementation of patient selection strategies based on these biomarkers is critical for clinical development. Capmatinib is also a rational combination partner for other kinase inhibitors to combat MET-driven resistance.

Chromosomal rearrangements of the mixed lineage leukemia (MLL/KMT2A) gene leading to oncogenic MLL-fusion proteins occur in ~10% of acute leukemias and are associated with poor clinical outcomes, emphasizing the need for new treatment modalities. Inhibition of the DOT1-like histone H3K79 methyltransferase (DOT1L) is a specific therapeutic approach for such leukemias that is currently being tested in clinical trials. However, in most MLL-rearranged leukemia models responses to DOT1L inhibitors are limited. Here, we performed deep-coverage short hairpin RNA sensitizer screens in DOT1L inhibitor-treated MLL-rearranged leukemia cell lines and discovered that targeting additional nodes of MLL complexes concomitantly with DOT1L inhibition bears great potential for superior therapeutic results. Most notably, combination of a DOT1L inhibitor with an inhibitor of the MLL-Menin interaction markedly enhanced induction of differentiation and cell killing in various MLL disease models including primary leukemia cells, while sparing normal hematopoiesis and leukemias without MLL rearrangements. Gene expression analysis on human and murine leukemic cells revealed that target genes of MLL-fusion proteins and MYC were suppressed more profoundly upon combination treatment. Our findings provide a strong rationale for a novel targeted combination therapy that is expected to improve therapeutic outcomes in patients with MLL-rearranged leukemia.

Inhibition of cyclin-dependent kinases 4 and 6 (CDK4/6) is associated with robust antitumor activity. Ribociclib (LEE011) is an orally bioavailable CDK4/6 inhibitor that is approved for the treatment of hormone receptor–positive, human epidermal growth factor receptor 2–negative advanced breast cancer, in combination with an aromatase inhibitor, and is currently being evaluated in several additional trials. Here, we report the preclinical profile of ribociclib.When tested across a large panel of kinase active site binding assays, ribociclib and palbociclib were highly selective for CDK4, while abemaciclib showed affinity to several other kinases. Both ribociclib and abemaciclib showed slightly higher potency in CDK4-dependent cells than in CDK6-dependent cells, while palbociclib did not show such a difference. Profiling CDK4/6 inhibitors in large-scale cancer cell line screens in vitro confirmed that RB1 loss of function is a negative predictor of sensitivity. We also found that routinely used cellular viability assays measuring adenosine triphosphate levels as a proxy for cell numbers underestimated the effects of CDK4/6 inhibition, which contrasts with assays that assess cell number more directly. Robust antitumor efficacy and combination benefit was detected when ribociclib was added to encorafenib, nazartinib, or endocrine therapies in patient-derived xenografts.

The histone 3 lysine 79 (H3K79) methyltransferase (HMT) DOT1L is known to play a critical role for growth and survival of MLL-rearranged leukemia. Serendipitous observations during high-throughput drug screens indicated that the use of DOT1L inhibitors might be expandable to multiple myeloma (MM). Through pharmacologic and genetic experiments, we could validate that DOT1L is essential for growth and viability of a subset of MM cell lines, in line with a recent report from another team. In vivo activity against established MM xenografts was observed with a novel DOT1L inhibitor. In order to understand the molecular mechanism of the dependency in MM, we examined gene expression changes upon DOT1L inhibition in sensitive and insensitive cell lines and discovered that genes belonging to the endoplasmic reticulum (ER) stress pathway and protein synthesis machinery were specifically suppressed in sensitive cells. Whole-genome CRISPR screens in the presence or absence of a DOT1L inhibitor revealed that concomitant targeting of the H3K4me3 methyltransferase SETD1B increases the effect of DOT1L inhibition. Our results provide a strong basis for further investigating DOT1L and SETD1B as targets in MM.

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A hallmark of cancer is unchecked cell division. Retinoblastoma protein (Rb) is a human tumor suppressor that guards a cell’s entry into S phase by binding E2F transcription factors and keeping them inactive. Many growth-promoting stimuli increase expression of D-type cyclins, which bind to and activate cyclin-dependent kinases 4 and 6 (CDK4/6). The cyclin D–bound CDK4/6 holoenzymes phosphorylate Rb, resulting in release of E2F, which in turn activates genes required for S phase entry and DNA replication. Numerous oncogenic aberrations converge at the CDK4/6–Rb pathway, providing a strong rationale for developing CDK4/6 inhibitors as cancer therapeutics. Ribociclib (LEE011) is a selective CDK4/6 inhibitor that has received FDA breakthrough therapy and priority review designations for treatment of hormone receptor–positive breast cancer in combination with letrozole and is being tested in additional clinical trials. Here we describe the preclinical selectivity profile of ribociclib in biochemical and cellular assays. Ribociclib inhibits both CDK4–cyclin D1 and CDK6–cyclin D3 kinase activity with nanomolar IC50s in biochemical assays. To comprehensively address the selectivity of ribociclib in direct comparison with 2 other clinical CDK4/6 inhibitors, palbociclib and abemaciclib, we made use of the KINOMEscan assay consisting of >450 kinase active site–directed competition-binding assays. We adjusted the test concentrations in the kinase-selectivity panel per the binding constants for CDK4 and CDK6 to account for the higher potency of abemaciclib. Data showed that both ribociclib and palbociclib have high selectivity for CDK4 (CDK6 was not covered in the panel), with very few distinct additional binding events detected. In contrast, abemaciclib is a much more promiscuous kinase inhibitor. Next, we sought to determine the relative potencies of the 3 inhibitors against CDK4 vs CDK6 in cellular assays. When testing different routinely used readouts of cellular viability, we found that assays that measured metabolic activity (eg, CTG) tended to underestimate the effects of CDK4/6 inhibition; thus, assays that either directly or indirectly assessed cell number were used instead. We first identified cancer cell lines primarily dependent on either CDK4 or CDK6 as judged by combined RNA expression analysis and shRNA or CRISPR-based functional assays. When determining IC50s of the 3 CDK4/6 inhibitors in these cell lines, we found that ribociclib and abemaciclib demonstrated greater activity in CDK4-dependent cells vs CDK6-dependent cells, whereas palbociclib was similarly active in both cell types. The high degree of CDK4 selectivity of ribociclib suggests that off-target kinase inhibition is an unlikely complication in patients. Moreover, the apparent preference for CDK4 over CDK6 could be an advantage in certain cancer types that are primarily dependent on CDK4. Citation Format: Ralph Tiedt, Scott Delach, Steven Kovats, Thomas Horn, Michael Acker, Barbara Schacher Engstler, Giordano Caponigro, Fei Su. Preclinical selectivity profile of the CDK4/6 inhibitor ribociclib (LEE011) compared with that of palbociclib and abemaciclib [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2346. doi:10.1158/1538-7445.AM2017-2346

<p>Supplementary text and figures Supplementary Figure 1 A, visualization of the "inflection point" (or EC50) and "Amax" parameters that are shown in Fig. 2A. B, HGF mRNA expression (by RNA-seq) vs HGF protein in culture supernatant for 76 cancer cell lines. Cell lines with high HGF mRNA expression generally led to increased protein levels in supernatant. U87-MG and IM95 are labeled, because in vivo efficacy data are presented for those models. U87-MG shows a remarkably high level of HGF protein secretion despite relatively low HGF mRNA. C, labeled cell lines scored as hits with at least 2 out of 4 MET inhibitors, each screened twice across a subset of the CCLE. Hits were defined as Amax {less than or equal to} â^'25% for all compounds, and inflection point {less than or equal to} 100 nmol/L for capmatinib, {less than or equal to} 1 ï�­mol/L for crizotinib and JNJ-38877605, and {less than or equal to} 500 nmol/L for PF-4217903. The upper panel shows MET vs HGF mRNA expression, while the lower panel shows MET expression vs MET copy number for the same cell lines. Three regions that among themselves contain all hits (amplified, overexpression, autocrine) were defined such that the hit with the lowest value for the respective expression or copy number value sets the cut-off. Number of hits compared to total number of cell lines in the respective regions are indicated in brackets. Colors as in Figure 2. D, Time course of MET phosphorylation after a 5 minute pulse treatment with 100 ng/mL recombinant HGF in 2 cell lines. NCI-H596 cells bear a MET exon14 skipping mutation while A549 cells do not. Supplementary Figure 2 A, MET dependency (x axis) vs MET gene copy number (y axis), downloaded from https://depmap.org. MET gene dependency was estimated by applying the DEMETER2 model to a combination of 3 large-scale RNAi screens (Broad Achilles, Novartis DRIVE, Marcotte et al.) (7). B, MET dependency (x axis) vs HGF mRNA expression by RNA-seq (y axis), downloaded from https://depmap.org. MET gene dependency was determined from pooled CRISPR screening data (Avana 1.0 library, Broad Institute) applying the CERES algorithm (8,9). Supplementary Figure 3 A, potency comparison of several clinical MET inhibitors in cellular proliferation assays with EBC-1 cells. Representative dose-response curves are shown on the left, numerical inflection point values (mean {plus minus} standard deviation, n = 3) are displayed on the right. B, MET mRNA expression measured by Affymetrix human genome U133 Plus 2.0 arrays (x axis) or RNA-seq (y axis) in 67 lung cancer PDX models (Supplementary Table 3). Identifiers of the 3 models with highest expression are indicated. C, same models as in B, but displaying MET mRNA by RNA-seq (x axis) vs MET copy number by Affymetrix SNP 6.0 array (y axis). D, data as in Fig. 3B but showing individual tumor volumes under treatment with capmatinib. E, mouse body weights corresponding to the experiment shown in Fig. 3B. F, data as in Fig. 3C but phospho- MET and total MET values from multi-spot ELISA shown separately. G, repeat of capmatinib efficacy study with lung PDX tumors bearing a MET exon 14 skipping mutation (model LU5381) as in Fig. 3D, but longer treatment duration. An average regression of ~60% was observed on day 12. A vehicle control was not repeated in this study. H, antitumor efficacy of capmatinib (dosed as indicated) against xenografts of the gastric cancer cell line IM95, which expresses HGF. Supplementary Figure 4 A, Loewe excess for data shown in Fig. 4C (upper panel), and % inhibition as well as Loewe excess for a combination matrix of capmatinib and the selective BCL2 inhibitor venetoclax (lower panel), in the cell line NCI-H1993. Percent dead cells were quantified by dual imaging with propidium iodide (PI) and Hoechst 33342. B, Percent dead cells by PI/Hoechst (upper panel) and Loewe excess (lower panel) for EBC-1 cells treated as in Fig. 4C and Supplementary Fig. 4A. C, Loewe excess for data shown in Fig. 4D, cell lines as indicated. Here, data are based on a CellTiter-Glo readout with quantification of seeded cells at time of compound addition ("growth inhibition" calculation). Loewe excess also refers to the "growth inhibition" data. D, treatment of EBC-1 cells with the indicated dose matrix of capmatinib and erlotinib. Experimental setup and analysis as in Fig. 4D (docetaxel combination). Supplementary Figure 5 A, HCC827 or HCC827 GR lung cancer cells were exposed to gefitinib, capmatinib, or combinations in a fixed ratio for 72 hours before measuring cell viability using a resazurin assay. The x axis label corresponds to gefitinib concentrations, while capmatinib was used at 10-fold lower concentrations due to its higher potency. In combination, gefitinib and capmatinib were mixed at a ratio of 10:1. B, HCC827 or NCI-H3255 cells were treated with a dilution series of gefitinib in the presence or absence of 50 ng/mL recombinant HGF. Cell viability was measured after 96 hours (HCC827) or 72 hours (NCIH3255) using a resazurin assay. The initial amount of viable cells was quantified at the time of compound addition (dashed line), and cell growth on the y axis is expressed as a multiple of this value. C, lysates of the lung cancer PDX model X-1787, either treated with vehicle or crizotinib, were incubated on a phospho-RTK array. Phospho-MET is clearly detectable in vehicle-treated lysate, suggesting that the high MET mRNA expression in this model leads to MET protein expression and activation. D, anti-tumor efficacy of crizotinib against X-1787 PDX tumors, characterized by presence of EML4-ALK and high MET expression. N = 4 per arm. E, RKO cells (BRAF V600E-mutant colorectal cancer cells secreting HGF) were exposed to capmatinib and fixed ratios of dabrafenib and trametinib in a dose matrix as indicated. After 3 days, viable cells were quantified by CellTiter-Glo. Inhibition is quantified in 2 different ways, without or with regard of the initial amount of viable cells at the time of compound addition (left and middle panel, respectively). Calculations are explained in detail in Materials and Methods. The right panel shows the Loewe excess for "% inhibition."</p>